# Automatic method for detection of solar coronal width using extreme ultra-violet (EUV) radiation

## TL;DR

This paper presents an automated image processing method to detect and measure the width of the solar corona in EUV images, aiding understanding of solar dynamics.

## Contribution

It introduces a novel automated segmentation technique using region growing to analyze coronal width and CME velocities from SOHO/EIT images.

## Key findings

- Coronal width varies with solar activity.
- Radial velocities of CMEs are successfully extracted.
- Method enables automated analysis of solar corona features.

## Abstract

Solar corona, the last main layer of the atmosphere of the Sun, is detectable in the EUV and X-ray. The corona is expanding into space up to millions of kilometers and is observable during the eclipse. The temperature is increasing about millions of Kelvin. The investigation of this layer is significant for solar physicists because it is dynamic and features. Active regions (AR) and solar mass ejections (CMEs) are the important features in the solar corona. In this research, the solar limb and coronal width is studied from full-disk images at $284 \AA$ taken by SOHO/EIT during eleven-year period (2000-2010). Next, using image processing methods and by applying region growing function, the corona is segmented and extracted from images in different angles. The radial velocities of CMEs are extracted.